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SimICD: A Closed-Loop Simulation Framework For ICD Therapy

Hannah Lydon, Milad Kazemi, Martin Bishop, Nicola Paoletti

TL;DR

SimICD delivers a closed-loop in silico framework that couples a virtual ICD decision engine with a detailed cardiac EP model to simulate therapy progression during tachyarrhythmias. It combines open-source electrophysiology simulations (OpenCARP) with device-manual–derived algorithms, enabling live signal monitoring, therapy prescription, and re-detection within a feedback loop. The study demonstrates a virtual patient cohort across NSR, focal VT, and re-entrant VT, showing that nominal ATP schemes can fail on faster VT and that episode-specific parameter tuning can terminate persistent VT. This framework provides a practical, tunable test-bed for ICD programming strategies and ATP protocol optimization with potential to reduce risks before clinical deployment.

Abstract

Virtual studies of ICD behaviour are crucial for testing device functionality in a controlled environment prior to clinical application. Although previous works have shown the viability of using in silico testing for diagnosis, there is a notable gap in available models that can simulate therapy progression decisions during arrhythmic episodes. This work introduces SimICD, a simulation tool which combines virtual ICD logic algorithms with cardiac electrophysiology simulations in a feedback loop, allowing the progression of ICD therapy protocols to be simulated for a range of tachy-arrhythmia episodes. Using a cohort of virtual patients, we demonstrate the ability of SimICD to simulate realistic cardiac signals and ICD responses that align with the logic of real-world devices, facilitating the reprogramming of ICD parameters to adapt to specific episodes.

SimICD: A Closed-Loop Simulation Framework For ICD Therapy

TL;DR

SimICD delivers a closed-loop in silico framework that couples a virtual ICD decision engine with a detailed cardiac EP model to simulate therapy progression during tachyarrhythmias. It combines open-source electrophysiology simulations (OpenCARP) with device-manual–derived algorithms, enabling live signal monitoring, therapy prescription, and re-detection within a feedback loop. The study demonstrates a virtual patient cohort across NSR, focal VT, and re-entrant VT, showing that nominal ATP schemes can fail on faster VT and that episode-specific parameter tuning can terminate persistent VT. This framework provides a practical, tunable test-bed for ICD programming strategies and ATP protocol optimization with potential to reduce risks before clinical deployment.

Abstract

Virtual studies of ICD behaviour are crucial for testing device functionality in a controlled environment prior to clinical application. Although previous works have shown the viability of using in silico testing for diagnosis, there is a notable gap in available models that can simulate therapy progression decisions during arrhythmic episodes. This work introduces SimICD, a simulation tool which combines virtual ICD logic algorithms with cardiac electrophysiology simulations in a feedback loop, allowing the progression of ICD therapy protocols to be simulated for a range of tachy-arrhythmia episodes. Using a cohort of virtual patients, we demonstrate the ability of SimICD to simulate realistic cardiac signals and ICD responses that align with the logic of real-world devices, facilitating the reprogramming of ICD parameters to adapt to specific episodes.
Paper Structure (19 sections, 3 equations, 7 figures, 2 tables, 2 algorithms)

This paper contains 19 sections, 3 equations, 7 figures, 2 tables, 2 algorithms.

Table of Contents

  1. Introduction
  2. Background
  3. ICD Functionality
  4. Electrophysiology Model
  5. ICD Modelling
  6. ICD Algorithms
  7. Therapy Simulations
  8. Closed Loop Automation
  9. Virtual Patient Cohort
  10. Mesh Preparation
  11. NSR Simulation
  12. Focal VT simulation
  13. Re-entrant VT Simulation
  14. Results
  15. Non-sustained VT
  16. ...and 4 more sections

Figures (7)

  • Figure 1: Visualization of SimICD simulation pipeline. Cardiac arrhythmia episodes are modelled in OpenCARP plank_opencarp_2021, the signals are extracted for analysis in the virtual ICD, and therapy decisions are relayed to the simulator.
  • Figure 2: Visualisation of the BiV mesh and the ICD electrodes
  • Figure 3: Voltage maps of the stages of a re-entrant circuit during VT simulations in openCARP. a) patient 2 and b) patient 3. From left to right: wavefront travels down through the isthmus and recirculates around the non-conducting scar tissue to re-enter.
  • Figure 4: Results of the RVOT episode simulation in patient 1. a) The EGM of the episode, with the NSR template shown for comparison for the shock trace. b) The evolution of the ventricular periods (blue), with the detection zones shown.
  • Figure 5: EGM traces for the (a) VT1 and (b) VT episodes and therapy interventions for Patient 2 (left ventricle scarring).
  • ...and 2 more figures